MétaCan
Menu
Back to cohort
Record W4324311145 · doi:10.4045/tidsskr.22.0521

Allogeneic stem cell transplantation in adults 2015–21

2023· article· en· W4324311145 on OpenAlexaff
Camilla Dao Vo, Anders Eivind Myhre, Ingerid Weum Abrahamsen, Mats Remberger, Jonas Mattsson, Yngvar Fløisand, Bjørn Christer Linder Grønvold, Geir E. Tjønnfjord, Tor Henrik Anderson Tvedt, Tobias Gedde‐Dahl

Bibliographic record

VenueTidsskrift for Den norske legeforening · 2023
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineTransplantationStem cellRetrospective cohort studyInternal medicineYoung adultSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Allogeneic stem cell transplantation is the only curative treatment for several malignant and non-malignant haematological diseases, and is associated with a risk of serious complications. In recent years, several changes have been introduced with the aim of reducing treatment-related complications. This retrospective study reviews quality indicators for patients who underwent transplantation in the period 2015-21. MATERIAL AND METHOD: The study included 589 adult patients who were treated with allogeneic stem cell transplantation for the first time at Oslo University Hospital in the period May 2015 to May 2021. Three two-year periods are compared using descriptive methods. RESULTS: In the period 2015-2021, the number of first-time transplant patients per year increased from 85 to 113. One-year survival increased from 68 % in the first two-year period to 74 % in the second period and 82 % in the last period. Both acute and chronic GVHD were reduced, and one-year GVHD-free and relapse-free survival increased from 42 % to 60 % during the study period. INTERPRETATION: Since 2015, the number of transplants has increased, while survival has improved and the risk of complications is lower.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.275
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueTidsskrift for Den norske legeforeningSame topicHematopoietic Stem Cell TransplantationFrench-language works237,207